LangChain Deployment AI Engineer

Role Description

Nexaminds is seeking a hands-on LangChain Deployment AI Engineer to join our full-time consulting team and deliver customer-facing generative and agentic AI solutions. This role is designed for an engineer who can translate an approved agentic AI architecture into reliable production grade agents, work effectively alongside LangChain architects, and embed with customer engineering, platform, security, data, and product teams.

The engineer will:

• Build and deploy applications using LangChain and LangGraph.
• Implement retrieval-augmented generation (RAG), agentic workflows, tool integrations, and evaluation pipelines.
• Own the operational details required to run those systems in production while monitoring agents using LangSmith.
• Deliver tested services, secure integrations, automated releases, observability, cost controls, runbooks, and measurable production outcomes.

Qualifications

• Bachelor’s degree in computer science, engineering, information systems, or a related discipline, or equivalent practical experience.
• Strong professional software-engineering experience with Python and/or JavaScript/TypeScript, including API development, asynchronous processing, testing, packaging, dependency management, and code review.
• Familiarity with the ADLC (Agent Development Life Cycle) and deploying configurable production-grade agents that can be managed and monitored in cloud platforms or on-prem datacenters.
• Hands-on experience building agents with LangChain and LangGraph, including chains/runnables, tools, MCP servers, structured outputs, stateful workflows, streaming, persistence, and error handling.
• Experience delivering LLM applications using commercial model APIs such as OpenAI, Anthropic, Google, or cloud-hosted equivalents, and/or open-source models.
• Practical experience with embeddings, vector search, hybrid retrieval, metadata filtering, reranking, document ingestion, grounding, and citation patterns.
• Experience with at least one vector database or search platform, such as Pinecone, Weaviate, Milvus, pgvector/PostgreSQL, Elasticsearch/OpenSearch, Redis, Azure AI Search, or a cloud-native equivalent.
• Production experience with Docker and Kubernetes and with at least one major cloud platform: AWS, Microsoft Azure, or Google Cloud Platform.
• Experience deploying production-grade agents and LLM applications beyond proofs of concept (POCs), including CI/CD, environment management, monitoring, incident troubleshooting, and operational support.
• Hands-on experience with LangSmith or comparable LLM tracing, evaluation, and observability tooling; ability to investigate quality, latency, cost, and tool/retrieval failures from traces.
• Working knowledge of application security, IAM, secrets management, encryption, API security, auditability, privacy, and secure software-development practices.
• Strong customer-facing communication, technical writing, and consulting skills, including the ability to work through ambiguity and explain tradeoffs to engineers and business stakeholders.
• Ability and willingness to travel to customer sites when an engagement requires it.

Requirements

• Experience with LangChain enterprise products and operating models, including LangSmith, Fleet and Deep Agents.
• Experience designing or implementing multi-agent systems, supervisor patterns, long-running workflows, durable execution, event-driven integration, and human approval steps.
• Experience with cloud AI platforms such as Amazon Bedrock, Azure AI Foundry/Azure OpenAI, Google Vertex AI, or managed Kubernetes platforms such as EKS, AKS, or GKE.
• Experience with infrastructure as code and delivery tooling such as Terraform, Helm, GitHub Actions, GitLab CI, Jenkins, Argo CD, or equivalent platforms.
• Experience with OpenTelemetry and observability platforms such as Datadog, Grafana, Prometheus, CloudWatch, Azure Monitor, or Google Cloud Operations.
• Knowledge of LLM evaluation methods, model/prompt versioning, red teaming, adversarial testing, hallucination analysis, retrieval evaluation, and human feedback programs.
• Experience in regulated or data-sensitive environments such as healthcare, financial services, insurance, manufacturing, or the public sector.
• Relevant cloud, Kubernetes, security, data engineering, or AI/ML certifications.

Benefits

• Stock options
• Remote work options
• Flexible working hours
• Benefits above the law

Company Description

Nexaminds is an AI and technology consulting company that helps organizations design, build, deploy, and operate production-grade generative and agentic AI solutions. We combine architecture, hands-on engineering, cloud delivery, and responsible AI practices to move customer initiatives from strategy and prototype to secure, production grade scalable business systems.